Hyper-personalization: The next level of personalized content

Hyper-personalization uses technology to personalize content and messages to an individual level.

Hyper-personalization increases engagement and loyalty by creating a unique customer experience for each user that is designed to exceed typical customer expectations.

Advances in AI algorithms, ML, data collection, and data analytics make hyper-personalization at scale possible. With the right tools, businesses can track customer behavior across multiple channels, analyze that behavior in real time, and combine that data with existing data to personalize content and messages in a way that is far more targeted than traditional personalization methods.

Hyper-personalization is how companies that are already delivering personalized experiences take their strategy to the next level. It leans heavily on technology to analyze data and deliver personalized content and unique experiences for each user.

This high level of personalization further increases customer engagement, boosts conversions, and builds loyalty.

Hyper-personalization can take many forms from personalizing a single experience based on previous purchase history to using predictive analytics to create hyper-personalized customer journeys in real time.

A great example is Netflix's use of hyper-personalization to take its personalized recommendations to the next level.

The streaming service wanted to enhance its customer recommendations by personalizing the artwork used for each movie title. Instead of choosing the best-performing artwork for each title across all audiences, they used online machine learning to tailor title images to each member. For example, if you watch a lot of romances, you might see more title images featuring couples. A friend who likes action movies or a particular actor will see different cover art for the same movie.

Hyper-personalization is all about going deeper with the personalized experience. It's a strategy for mature companies that are already collecting data, creating customer profiles, and delivering tailored content.

AI tools become critical, enabling teams to create, manage, and deliver all the different content iterations needed for hyper-personalization.

For example, Contentful helps leading brands like Ruggable, deliver personalized experiences at scale with an AI-native personalization platform. Using the Contentful platform, Ruggable personalizes its homepage with different experiences for dog and cat owners.

Using Contentful, Ruggable could take this to the level of hyper-personalization in a few ways.

One dimension of hyper-personalization would be to personalize the experience for every campaign—not just cat and dog-related campaigns.

A second dimension would be a more granular personalized experience, such as featuring specific dog breeds based on customer data or layering in personalization based on location data so cat-related campaigns for city-based visitors are differentiated from those targeting rural cat owners.

It's all about getting more granular with the segmentation rules, adding additional "and" rules to the segmentation that further personalize each individual's experience.

Ninetailed by Contentful empowers businesses to create AI-native personalized experiences across channels, all inside Contentful. By pulling together content management, data integration, and personalization into one unified tool, Contentful helps businesses launch hyper-personalized experiences faster.

Learn how Contentful is helping brands increase ROI with cutting-edge personalization tools.

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